Priesemann, Viola, Dr.

Max Planck Research Group Leader Neural Systems Theory


  • Since 2016: Max Planck Research Group Leader, MPI for Dynamics and Self-Organization, Göttingen, Germany
  • 01/2017 – 03/2017: Guest Researcher, Ernst-Strüngmann-Institute, Frankfurt
  • 2014 – 2016: Bernstein Fellow and Group Leader, Bernstein Center for Computational Neuroscience & MPI for Dynamics and Self-Organization, Göttingen, Germany
  • 2013 – 2014: PostDoc, MPI for Dynamics and Self-Organization, Göttingen, Germany
  • 2013: PhD, Goethe University Frankfurt, Germany
  • 2008 – 2013: Research Projects at the Ecole Normale Superieure (Paris, France), Caltech
    Pasadena, USA), MPI for Brain Research & FIAS (Frankfurt, Germany)



Honours, Grants & Service to the Community


  • since 2020: Member of the Cluster of Excellence: Multiscale Bioimaging
  • since 2020: Associated to the Max Planck - U of Toronto Centre of Neurophysics
  • since 2020: Lead-PI in a project of the SPP 2205 “Evolutionary Optimisation of Neuronal
    Processing”




Major Research Interests

Neural Networks
Information Processing
Statistical Physics
Nonlinear Dynamics
Collective Phenomena
Living Computation
Self-Organization of Computation
Neural Plasticity & Learning
Homeostatic Plasticity
Design and Optimization of Neural Computation
Information Theory
Bayesian Inference
COVID-19



Homepage Department/Research Group


http://www.viola-priesemann.de/

Link to my google scholar profile:

https://scholar.google.de/citations?user=5oK8Ek4AAAAJ&hl=de&oi=ao


Selected Recent Publications



  • J Dehning, J Zierenberg, FP Spitzner, M Wibral, JP Neto, M Wilczek, V Priesemann, “Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions”, Science, 2020.

  • B Cramer, D Stöckel, M Kreft, M Wibral, J Schemmel, K Meier & V Priesemann, “Control of criticality and computation in spiking neuromorphic networks with plasticity”, Nature Communications, 2020

  • J Wilting & V Priesemann, “Between Perfectly Critical and Fully Irregular: A Reverberating Model Captures and Predicts Cortical Spike Propagation”, Cerebral Cortex, 2019.

  • J Wilting & V Priesemann, “Inferring collective dynamical states from widely unobserved systems”, Nature Communications, 2018.

  • J Zierenberg, J Wilting, V Priesemann, “Homeostatic Plasticity and External Input Shape Neural Network Dynamics”, Physical Review X, 2018.

  • A Levina & V Priesemann, “Subsampling scaling”, Nature Communications 2017.

  • V Priesemann et al., “Spike avalanches in vivo suggest a driven, slightly subcritical brain state”, Frontiers in Systems Neuroscience, 2014.